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Dynamic 2D/3D Registration
(The Eurographics Association, 2014) Bouaziz, Sofien; Tagliasacchi, Andrea; Pauly, Mark; Nicolas Holzschuch and Karol Myszkowski
Image and geometry registration algorithms are an essential component of many computer graphics and computer vision systems. With recent technological advances in RGB-D sensors, such as the Microsoft Kinect or Asus Xtion Live, robust algorithms that combine 2D image and 3D geometry registration have become an active area of research. The goal of this course is to introduce the basics of 2D/3D registration algorithms and to provide theoretical explanations and practical tools to design computer vision and computer graphics systems based on RGB-D devices. To illustrate the theory and demonstrate practical relevance, we briefly discuss three applications: rigid scanning, non-rigid modeling, and realtime face tracking. Our course targets researchers and computer graphics practitioners with a background in computer graphics and/or computer vision. An up-to-date version of the course notes as well as slides and source code can be found at http://lgg.epfl.ch/2d3dRegistration.
Sparse Iterative Closest Point
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Bouaziz, Sofien; Tagliasacchi, Andrea; Pauly, Mark; Yaron Lipman and Hao Zhang
Rigid registration of two geometric data sets is essential in many applications, including robot navigation, surface reconstruction, and shape matching. Most commonly, variants of the Iterative Closest Point (ICP) algorithm are employed for this task. These methods alternate between closest point computations to establish correspondences between two data sets, and solving for the optimal transformation that brings these correspondences into alignment. A major difficulty for this approach is the sensitivity to outliers and missing data often observed in 3D scans. Most practical implementations of the ICP algorithm address this issue with a number of heuristics to prune or reweight correspondences. However, these heuristics can be unreliable and difficult to tune, which often requires substantial manual assistance. We propose a new formulation of the ICP algorithm that avoids these difficulties by formulating the registration optimization using sparsity inducing norms. Our new algorithm retains the simple structure of the ICP algorithm, while achieving superior registration results when dealing with outliers and incomplete data. The complete source code of our implementation is provided at http://lgg.epfl.ch/sparseicp.
Self Tuning Texture Optimization
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Kaspar, Alexandre; Neubert, Boris; Lischinski, Dani; Pauly, Mark; Kopf, Johannes; Olga Sorkine-Hornung and Michael Wimmer
The goal of example-based texture synthesis methods is to generate arbitrarily large textures from limited exemplars in order to fit the exact dimensions and resolution required for a specific modeling task. The challenge is to faithfully capture all of the visual characteristics of the exemplar texture, without introducing obvious repetitions or unnatural looking visual elements. While existing non-parametric synthesis methods have made remarkable progress towards this goal, most such methods have been demonstrated only on relatively low-resolution exemplars. Real-world high resolution textures often contain texture details at multiple scales, which these methods have difficulty reproducing faithfully. In this work, we present a new general-purpose and fully automatic selftuning non-parametric texture synthesis method that extends Texture Optimization by introducing several key improvements that result in superior synthesis ability. Our method is able to self-tune its various parameters and weights and focuses on addressing three challenging aspects of texture synthesis: (i) irregular large scale structures are faithfully reproduced through the use of automatically generated and weighted guidance channels; (ii) repetition and smoothing of texture patches is avoided by new spatial uniformity constraints; (iii) a smart initialization strategy is used in order to improve the synthesis of regular and near-regular textures, without affecting textures that do not exhibit regularities. We demonstrate the versatility and robustness of our completely automatic approach on a variety of challenging high-resolution texture exemplars.
Fabrication-aware Design with Intersecting Planar Pieces
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Schwartzburg, Yuliy; Pauly, Mark; I. Navazo, P. Poulin
We propose a computational design approach to generate 3D models composed of interlocking planar pieces. We show how intricate 3D forms can be created by sliding the pieces into each other along straight slits, leading to a simple construction that does not require glue, screws, or other means of support. To facilitate the design process, we present an abstraction model that formalizes the main geometric constraints imposed by fabrication and assembly, and incorporates conditions on the rigidity of the resulting structure.We show that the tight coupling of constraints makes manual design highly nontrivial and introduce an optimization method to automate constraint satisfaction based on an analysis of the constraint relation graph. This algorithm ensures that the planar parts can be fabricated and assembled. We demonstrate the versatility of our approach by creating 3D toy models, an architectural design study, and several examples of functional furniture.
Symmetry in Shapes - Theory and Practice
(The Eurographics Association, 2013) Mitra, Niloy; Ovsjanikov, Maksim; Pauly, Mark; Wand, Michael; Ceylan, Duygu; Diego Gutierrez and Karol Myszkowski
Part I: What is symmetry? Part II: Extrinsic symmetry detection Part III: Intrinsic symmetries Part IV: Representations and applications Conclusions, wrap-up
Thumbnail Galleries for Procedural Models
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Lienhard, Stefan; Specht, Matthias; Neubert, Boris; Pauly, Mark; Müller, Pascal; B. Levy and J. Kautz
Procedural modeling allows for the generation of innumerable variations of models from a parameterized, conditional or stochastic rule set. Due to the abstractness, complexity and stochastic nature of rule sets, it is often very difficult to have an understanding of the diversity of models that a given rule set defines. We address this problem by presenting a novel system to automatically generate, cluster, rank, and select a series of representative thumbnail images out of a rule set. We introduce a set of view attributes that can be used to measure the suitability of an image to represent a model, and allow for comparison of different models derived from the same rule set. To find the best thumbnails, we exploit these view attributes on images of models obtained by stochastically sampling the parameter space of the rule set. The resulting thumbnail gallery gives a representative visual impression of the procedural modeling potential of the rule set. Performance is discussed by means of a number of distinct examples and compared to state-of-the-art approaches.
Symmetry in 3D Geometry: Extraction and Applications
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Mitra, Niloy J.; Pauly, Mark; Wand, Michael; Ceylan, Duygu; Holly Rushmeier and Oliver Deussen
The concept of symmetry has received significant attention in computer graphics and computer vision research in recent years. Numerous methods have been proposed to find, extract, encode and exploit geometric symmetries and high‐level structural information for a wide variety of geometry processing tasks. This report surveys and classifies recent developments in symmetry detection. We focus on elucidating the key similarities and differences between existing methods to gain a better understanding of a fundamental problem in digital geometry processing and shape understanding in general. We discuss a variety of applications in computer graphics and geometry processing that benefit from symmetry information for more effective processing. An analysis of the strengths and limitations of existing algorithms highlights the plenitude of opportunities for future research both in terms of theory and applications.The concept of symmetry has received significant attention in computer graphics and computer vision research in recent years. Numerous methods have been proposed to find, extract, encode, and exploit geometric symmetries and high‐level structural information for a wide variety of geometry processing tasks. This report surveys and classifies recent developments in symmetry detection. We focus on elucidating the key similarities and differences between existing methods to gain a better understanding of a fundamental problem in digital geometry processing and shape understanding in general.
Robust Articulated-ICP for Real-Time Hand Tracking
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Tagliasacchi, Andrea; Schröder, Matthias; Tkach, Anastasia; Bouaziz, Sofien; Botsch, Mario; Pauly, Mark; Mirela Ben-Chen and Ligang Liu
We present a robust method for capturing articulated hand motions in realtime using a single depth camera. Our system is based on a realtime registration process that accurately reconstructs hand poses by fitting a 3D articulated hand model to depth images. We register the hand model using depth, silhouette, and temporal information. To effectively map low-quality depth maps to realistic hand poses, we regularize the registration with kinematic and temporal priors, as well as a data-driven prior built from a database of realistic hand poses. We present a principled way of integrating such priors into our registration optimization to enable robust tracking without severely restricting the freedom of motion. A core technical contribution is a new method for computing tracking correspondences that directly models occlusions typical of single-camera setups. To ensure reproducibility of our results and facilitate future research, we fully disclose the source code of our implementation.
Factored Facade Acquisition using Symmetric Line Arrangements
(The Eurographics Association and John Wiley and Sons Ltd., 2012) Ceylan, Duygu; Mitra, Niloy J.; Li, Hao; Weise, Thibaut; Pauly, Mark; P. Cignoni and T. Ertl
We introduce a novel framework for image-based 3D reconstruction of urban buildings based on symmetry priors. Starting from image-level edges, we generate a sparse and approximate set of consistent 3D lines. These lines are then used to simultaneously detect symmetric line arrangements while refining the estimated 3D model. Operating both on 2D image data and intermediate 3D feature representations, we perform iterative feature consolidation and effective outlier pruning, thus eliminating reconstruction artifacts arising from ambiguous or wrong stereo matches. We exploit non-local coherence of symmetric elements to generate precise model reconstructions, even in the presence of a significant amount of outlier image-edges arising from reflections, shadows, outlier objects, etc. We evaluate our algorithm on several challenging test scenarios, both synthetic and real. Beyond reconstruction, the extracted symmetry patterns are useful towards interactive and intuitive model manipulations.
Design Transformations for Rule-based Procedural Modeling
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Lienhard, Stefan; Lau, Cheryl; Müller, Pascal; Wonka, Peter; Pauly, Mark; Loic Barthe and Bedrich Benes
We introduce design transformations for rule-based procedural models, e.g., for buildings and plants. Given two or more procedural designs, each specified by a grammar, a design transformation combines elements of the existing designs to generate new designs. We introduce two technical components to enable design transformations. First, we extend the concept of discrete rule switching to rule merging, leading to a very large shape space for combining procedural models. Second, we propose an algorithm to jointly derive two or more grammars, called grammar co-derivation. We demonstrate two applications of our work: we show that our framework leads to a larger variety of models than previous work, and we show fine-grained transformation sequences between two procedural models.

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